Modelling decision-making within rail maintenance control rooms

Nastaran Dadashi,David Golightly,Sarah Sharples

doi:10.1007/s10111-020-00636-x

Nastaran Dadashi, David Golightly + Show 1 more

Open Access

https://doi.org/10.1007/s10111-020-00636-x

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Abstract

This paper presents a cognitive task analysis to derive models of decision-making for rail maintenance processes. Maintenance processes are vital for safe and continuous availability of rail assets and services. These processes are increasingly embracing the ‘Intelligent Infrastructure’ paradigm, which uses automated analysis to predict asset state and potential failure. Understanding the cognitive processes of maintenance operators is critical to underpin design and acceptance of Intelligent Infrastructure. A combination of methods, including observation, interview and an adaptation of critical decision method, was employed to elicit the decision-making strategies of operators in three different types of maintenance control centre, with three configurations of pre-existing technology. The output is a model of decision-making, based on Rasmussen’s decision ladder, that reflects the varying role of automation depending on technology configurations. The analysis also identifies which types of fault were most challenging for operators and identifies the strategies used by operators to manage the concurrent challenges of information deficiencies (both underload and overload). Implications for design are discussed.

Highlights

Railway Maintenance Control Centres are responsible for ensuring the continuous availability of infrastructure assets
Technological advances, including Remote Condition Monitoring (RCM) systems, are commonly used within these centres to provide reliable, real-time data regarding the status of assets and, to enhance operators’ situation awareness and decision-making
The question remains as to whether introducing these technological advances will lead to a change in the way operators make decisions when they are conducting cognitive processing associated with fault finding

Summary

Introduction

Railway Maintenance Control Centres are responsible for ensuring the continuous availability of infrastructure assets. Technological advances, including Remote Condition Monitoring (RCM) systems, are commonly used within these centres to provide reliable, real-time data regarding the status of assets and, to enhance operators’ situation awareness and decision-making These control environments are embracing predictive maintenance and ‘Intelligent Infrastructure’ (Pedregal et al 2004; Ollier 2006; Dadashi et al 2014). Technology adoption and efficient utilisation of Intelligent Infrastructure is, dependent on careful alignment with operators’ expertise, decision-making and major coping strategies Does this help the acceptance process, many of these coping strategies indicate the important constraints, such as workload or gaps in information, that shape the way operators work

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